Special Section on Optical Diagnostic and Biophotonic Methods from Bench to Bedside

Semiautomatic segmentation and quantification of calcified plaques in intracoronary optical coherence tomography images

[+] Author Affiliations
Zhao Wang

Case Western Reserve University, Department of Biomedical Engineering, 10900 Euclid Avenue, Cleveland, Ohio 44106

Hiroyuki Kyono, Hiram G. Bezerra

University Hospitals Case Medical Center, Harrington-McLaughlin Heart & Vascular Institute, 11100 Euclid Avenue, Cleveland, Ohio 44106

Hui Wang, Madhusudhana Gargesha

Case Western Reserve University, Department of Biomedical Engineering, 10900 Euclid Avenue, Cleveland, Ohio 44106

Chadi Alraies

Case Western Reserve University, Learner College of Medicine, 10900 Euclid Avenue, Cleveland, Ohio 44106

Chenyang Xu, Joseph M. Schmitt

Lightlab Imaging Incorporated, 1 Technology Park Drive, Westford, Massachusetts 01886

David L. Wilson

Case Western Reserve University, Department of Biomedical Engineering, 10900 Euclid Avenue, Cleveland, Ohio 44106

Marco A. Costa

University Hospitals Case Medical Center, Harrington-McLaughlin Heart & Vascular Institute, 11100 Euclid Avenue, Cleveland, Ohio 44106

Andrew M. Rollins

Case Western Reserve University, Department of Biomedical Engineering, 10900 Euclid Avenue, Cleveland, Ohio 44106

J. Biomed. Opt. 15(6), 061711 (November 22, 2010). doi:10.1117/1.3506212
History: Received February 10, 2010; Revised August 09, 2010; Accepted September 15, 2010; Published November 22, 2010; Online November 22, 2010
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Coronary calcified plaque (CP) is both an important marker of atherosclerosis and major determinant of the success of coronary stenting. Intracoronary optical coherence tomography (OCT) with high spatial resolution can provide detailed volumetric characterization of CP. We present a semiautomatic method for segmentation and quantification of CP in OCT images. Following segmentation of the lumen, guide wire, and arterial wall, the CP was localized by edge detection and traced using a combined intensity and gradient-based level-set model. From the segmentation regions, quantification of the depth, area, angle fill fraction, and thickness of the CP was demonstrated. Validation by comparing the automatic results to expert manual segmentation of 106 in vivo images from eight patients showed an accuracy of 78±9%. For a variety of CP measurements, the bias was insignificant (except for depth measurement) and the agreement was adequate when the CP has a clear outer border and no guide-wire overlap. These results suggest that the proposed method can be used for automated CP analysis in OCT, thereby facilitating our understanding of coronary artery calcification in the process of atherosclerosis and helping guide complex interventional strategies in coronary arteries with superficial calcification.

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© 2010 Society of Photo-Optical Instrumentation Engineers

Citation

Zhao Wang ; Hiroyuki Kyono ; Hiram G. Bezerra ; Hui Wang ; Madhusudhana Gargesha, et al.
"Semiautomatic segmentation and quantification of calcified plaques in intracoronary optical coherence tomography images", J. Biomed. Opt. 15(6), 061711 (November 22, 2010). ; http://dx.doi.org/10.1117/1.3506212


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